A CNN stereo vision hardware system for autonomous robot navigation

Abstract

The high parallel analogue processing rate makes the cellular neural networks paradigm really useful in such a problems where real-time replies to external stimuli are required. The development of an effective system for autonomous robot navigation can find a valid support from this research. Moreover, the growth of new CNN algorithms can afford the necessary feedback to the hardware developers to improve their realisations. In this paper some measurements of a stereo-vision algorithm on a CNN hardware implementation (the 720DPCNN system) are given.